Gemma 3 27B
Google · Text generation · 27B · 131k context · Released 12 March 2025
Permitted with conditions
Open weights
Runs on CPU
Apple Silicon
Gemma 3 27B is the sweet spot of Google's open model family: capable enough to be a genuine general-purpose model, small enough to run on one high-end consumer card. It accepts images alongside text and has a 128k context window. Google publishes quantisation-aware-trained checkpoints, so the 4-bit versions hold up better than a naive quantisation would.
Strengths
- Strong general model that also understands images
- Fits a single 24GB card at 4-bit, with official quantisation-aware weights
- Very broad language support, over 140 languages
Weaknesses
- The Gemma licence carries use conditions, unlike Apache 2.0 models
- Image understanding is capable but not its main strength
- A 27B model needs a good card, not a laptop, for usable quality
Hardware requirements
| Quantisation | Approx. VRAM | Notes |
|---|---|---|
| Q4_K_M | ~15GB | Fits a 24GB card, official quantisation-aware weights available |
| Q5_K_M | ~19GB | Better quality, still fits 24GB with modest context |
| Q8_0 | ~28GB | Near-lossless, needs 32GB or more |
| FP16 | ~54GB | Full precision, server or multi-GPU territory |
Also runs on CPU (slower). Optimised builds available for Apple Silicon.
Licence
Gemma Terms of Use — read the licence
Availability
- Official page
- Hugging Face
- ollama run gemma3:27b
Recommended for
- A single-card 24GB general model that also handles images
- Multilingual work across many languages
- Users who want a capable Google model with official 4-bit weights
Related guides
Glossary
Catalogue entry last verified 30 July 2026. Specifications change; verify anything you are about to spend money on.